ANEXO I

Ofrecemos un listado de bibliografía donde se pueden encontrar las "instrucciones" para manejar más adecuadamente la caja de herramientas, lo que nos ayudará a escoger la herramienta más adecuada para cada problema.

Sobre estadística clásica y ecología cuantitativa básica

Piñol, J. & Martínez-Vilalta, J. 2006. Ecología con números: una introducción a la ecología con problemas y ejercicios de simulación. Lynx Edicions, Barcelona.

Zar, J.H. 1996. Biostatistical Analysis. 3rd edn. Upper Saddle River, New Jersey.

Sobre diseño experimental

Quinn, G.P. & Keough, M.J. 2004. Experimental design and data analysis for biologists. Cambridge University Press, Cambridge.

Scheiner, S.M. & Gurevitch, J. 2001. Design and analysis of ecological experiments. Oxford University Press, Oxford.

Steidl, R.J., Hayes, J.P. & Schauber, E. 1997. Statistical power analysis in wildlife research. J. Wildlife Manage. 61: 270-279.

Sobre críticas al contraste clásico de hipótesis

Fidler, F., Burgman, M.A., Cumming, G., Buttrose, R, & Thomason, N. 2006. Impact of criticism of null-hypothesis significance testing on statistical reporting practices in conservation biology. Conserv. Biol. 20: 1539-1544.

Germano, J. D. 1999. Ecology, statistics, and the art of misdiagnosis: The need for a paradigm shift. Environ. Rev. 7: 167-190.

Gigerenzer, G. 2004. Mindless statistics. The Journal of Socio-Economics 33: 587-606.

Harlow, L.L., Mulaik, S.A. & Steiger, J.H. (Eds.). 1997. What if there were no significance tests? Lawrence Erlbaum Associates, Publishers, London.

Hobbs, N.T. & Hilborn, R. 2006. Alternatives to statistical hypothesis testing in ecology: a guide to self teaching. Ecol. Appl. 16: 5-19.

James, F.C. & McCullogh, C.E. 1990. Multivariate analysis in ecology and systematics: Panacea or Pandora's box? Annu. Rev. Ecol. Sys. 21: 129-166.

Johnson, D.H. 1999. The insignificance of statistical significance testing. J. Wildlife Manage. 63: 763-772.

Lukacs, P.M., Thompson, W.L., Kendall, W.L., Gould, W.R., Doherty, P.F., Burnham, K.P. & Anderson, D.R. 2007. Concerns regarding a call for pluralism of information theory and hypothesis testing. J. Appl. Ecol. 44: 456-460.

Martínez-Abraín, A. & Oro. D. 2005. Can ornithology advance as a science relying on significance testing? A literature review in search of a consensus. Ardeola 52: 377-387.

Martínez-Abraín, A. 2007. Are there any differences? A non-sensical question in ecology. Acta Oecol. 32: 203-206.

Martínez-Abraín, A. 2008. Statistical significance and biological relevance: A call fo a more cautious interpretation of results in ecology. Acta Oecologica (In press).

Stephens, P.A., Buskirk, S.W., Hayward, G.D. & Martínez del Río, C. 2005. Information theory and hypothesis testing: a call for pluralism. J.Appl. Ecol. 42: 4-12.

Stephens, P.A., Buskirk, S.W. & Martínez del Río, C. 2006. Inference in ecology and evolution. Trends Ecol. Evol. 22: 192-197.

Williams, B.K., Nichols, J.D. & Conroy, M.J. 2001. Analysis and management of animal populations. Academic Press, London

Sobre intervalos de confianza

Belia, S., Fidler, F., Williams, J. & Cumming. G. 2005. Researchers misunderstand confidence intervals and standard error bars. Psychol. Meth. 10: 389-396.

Cumming, G. & Finch, S. 2005. Confidence intervals and how to read pictures of data. Am. psychol 60: 170-180.

Cumming, G., Fidler, F. & Vaux, D.L. 2007. Error bars in experimental biology. J. Cell Biol. 177: 7-11.

Sobre criterios de información teórica.

Anderson, D.R. & Burnham, K.P. 2002. Avoiding pitfalls when using information-theoretic methods. J. Wildlife Manage. 66: 912-918.

Anderson, D.R., Burnham, K.P. & Thompson, W.L. 2000. Null hypothesis testing: problems, prevalence, and an alternative. J. Wildlife Manage. 64: 912-923.

Anderson, D.R., Burnham, K.P. & White, G.C. 2001. Kullback-Leibler information in resolving natural resource conflicts when definitive data exist. Wildlife Soc B 29: 1260-1270.

Anderson, D.R., Link, W.A., Johnson, D.H. & Burnham, K.P. 2001. Suggestions for presenting the result of data analyses. J. Wildlife Manage. 65: 373-378.

Burnham, K.P. & Anderson, D.R. 2001. Kullback-Leibler information as a basis for strong inference in ecological studies. Wildlife Res. 28: 111-119.

Burnham, K.P. & Anderson, D.R. 2002. Model selection and multi-model inference: a practical information theoretic approach. Springer-Verlag, New York.

Burnham, K.P. & Anderson, D.R. 2004. Multimodel Inference: understanding AIC and BIC in model selection. Sociol. Meth. & Res. 33: 261-304.

Hilborn, R. & Mangel, M. 1997. The ecological detective: Confronting models with data. Princeton University Press, Princeton.

Stephens, P.A., Buskirk, S.W., Hayward, G.D. & Martínez del Río, C. 2005. Information theory and hypothesis testing: a call for pluralism. J. Appl. Ecol. 42: 4-12.

Sobre estadística Bayesiana

Brooks, S.P., King, R. & Morgan, B.J.Y. 2004. A Bayesian approach to combining animal abundance and demographic data. Anim. Biodivers. Conserv. 27: 515-529.

Clark, J.S. 2005. Why environmental scientists are becoming Bayesians? Ecol. Lett. 8: 2-14.

Ellison, A.M. 1996. An introduction to Bayesian inference for ecological research and environmental decision-making. Ecol. Appl 6: 1036-1046.

Gelman, A., Carlin, J.B., Stern, H.S. & Rubin, D.B. (Eds.). 2004. Bayesian data analysis. Chapman & Hall, London.

King, R. & Brooks, S.P. 2004. Bayesian analysis of the Hector's Dolphin data. Anim. Biodivers. Conserv. 27: 343-354.

Link, W.A., Cam, E., Nichols, J.D. & Cooch, E.G. 2002. On bugs and birds: Markov Chain Monte Carlo for hierarchical modelling in wildlife research. J. Wildlife Manage. 66: 277–291.

McCarthy, M.A. 2007. Bayesian methods for ecology. Cambridge University Press, New York.

McCarthy, M.A. & Masters, P. 2005. Profiting from prior information in Bayesian analyses of ecological data. J. Appl. Ecol. 42: 1012-1019.

Wade, P.R. 2000. Bayesian methods in conservation biology. Conserv. Biol. 14: 1308-1316.